Decoding speech from spike-based neural population recordings in secondary auditory cortex of non-human primates
Abstract
Direct electronic communication with sensory areas of the neocortex is a challenging ambition for brain-computer interfaces. Here, we report the first successful neural decoding of English words with high intelligibility from intracortical spike-based neural population activity recorded from the secondary auditory cortex of macaques. We acquired 96-channel full-broadband population recordings using intracortical microelectrode arrays in the rostral and caudal parabelt regions of the superior temporal gyrus (STG). We leveraged a new neural processing toolkit to investigate the choice of decoding algorithm, neural preprocessing, audio representation, channel count, and array location on neural decoding performance. The presented spike-based machine learning neural decoding approach may further be useful in informing future encoding strategies to deliver direct auditory percepts to the brain as specific patterns of microstimulation.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Dec 11, 2019
- Source ID
- 10.1038/s42003-019-0707-9
Entities
People
- A. V. Nurmikko
- Christopher Heelan
- David M. Brandman
- Ji-Hun Lee
- Laurie Lynch
- Ronan O’shea
- Wilson Truccolo
Organizations
- United States Department of Defense